Re: Add softplus implementation in scipy.special

Hi Aadya,

Thank you for sending the email. This is in reference to the issue: https://github.com/scipy/scipy/issues/17905

Note that we cannot use code from StackOverflow due to licensing incompatibilities. See here for more details https://scipy.github.io/devdocs/dev/hacking.html#license-considerations

Cheers,
Pamphile


> On 13.04.2023, at 10:28, [email protected] wrote:
> 
> Hello Everyone,
> It might be nice to have a numerically stable softplus implementation, ie np.log1p(np.exp(x))
> 
> This implementation can be based on the following stackoverflow answers :
> https://cs.stackexchange.com/questions/110798/numerically-stable-log1pexp-calculation
> https://stackoverflow.com/questions/44230635/avoid-overflow-with-softplus-function-in-python
> 
> It can have a good place in the scipy module as it has other applications apart from ML/AI like it's a quite natural penalty function in optimization if one desires a smooth penalty in some optimization problems.
> 
> All opinions are welcome. Let's discuss this?
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